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Updated: Jul 16, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Factors Predicting Survival in ALS Patients--Data from a Population-Based Registry in Rhineland-Palatinate, Germany
Joachim Wolf1, Anton Safer, Johannes C Wöhrle
1Department of Neurology, Diakonissenkrankenhaus Mannheim, Mannheim, Germany.
Background:
The possibility to survive with amyotrophic lateral sclerosis (ALS) varies considerably and survival extends from a few months to several years. A number of demographic and clinical factors predicting survival have been described; however, existing data are conflicting. We intended to predict patient survival in a population-based prospective cohort of ALS patients from variables known up to the time of diagnosis.
Methods:
Incident ALS patients diagnosed within three consecutive years were enrolled and regularly followed up. Candidate demographic and disease variables were analysed for survival probability using the Kaplan-Meier method. The Cox proportional hazard regression model was used to assess the influence of selected predictor variables on survival prognosis.
Results:
In the cohort of 193 patients (mean age 65.8, standard deviation 10.2 years), worse prognosis was independently predicted by older age, male gender, bulbar onset, probable or definite ALS according to El Escorial criteria, shorter interval between symptom onset and diagnosis, lower Functional Rating Scale, diagnosis of frontotemporal dementia, and living without a partner.
Conclusions:
Taking into account these predictor variables, an approximate survival prognosis of individual ALS patients at diagnosis seems feasible.
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